Musico

A Python script that automatically identifies music playing in the environment using Shazam. Works on both Raspberry Pi and macOS.

Features

• Samples audio every 60 seconds from the default audio input
• Detects silence and skips processing when no music is playing
• Uses Shazam API to identify music tracks
• Displays track information and cover art in a GUI
• Comprehensive logging for debugging
• Runs in isolated virtual environment
• Cross-platform support (Raspberry Pi and macOS)

Requirements

• Raspberry Pi: Audio input capability, Python 3.7+
• macOS: Built-in microphone or external audio input, Python 3.7+
• Internet connection for Shazam API calls

Quick Setup

For Raspberry Pi:

1. Clone or download this repository to your Raspberry Pi
2. Run the setup script:

chmod +x setup.sh
./setup.sh

For macOS:

1. Clone or download this repository to your Mac
2. Run the setup script:

chmod +x setup.sh
./setup.sh

The setup script will automatically:

• Detect your operating system
• Install system dependencies (via apt on Linux, Homebrew on macOS)
• Create a virtual environment
• Install all Python packages

Usage

Option 1: Using the run script (recommended)

./run.sh

Option 2: Manual activation

# Activate virtual environment
source music_env/bin/activate

# Run the script
python music_identifier.py

# Deactivate when done
deactivate

Testing Your Setup

After setup, you can test if everything is working by running Musico:

./run.sh

The application will start and begin sampling audio. Check the console output for any error messages.

The script will:

1. Start a GUI window showing the current status
2. Begin sampling audio every 60 seconds
3. Display identified tracks with cover art
4. Log all activity to Musico.log

Tools

Musico includes several helpful tools:

• adjust_threshold.py - Interactive threshold adjustment tool
• select_input.py - Audio input device selector
• run.sh - Easy startup script
• setup.sh - Cross-platform installation script

Configuration

You can adjust these parameters in config.py:

• RECORD_DURATION: Length of audio sample (default: 10 seconds)
• SILENCE_THRESHOLD: Sensitivity for silence detection (default: 0.0001)
• SAMPLE_RATE: Audio sample rate (default: 44100 Hz)

If Musico is too sensitive or not sensitive enough, you can adjust the SILENCE_THRESHOLD value:

Option 1: Use the adjustment tool (recommended)

python adjust_threshold.py

Option 2: Edit config.py manually

• Lower values (e.g., 0.0001) = more sensitive to quiet sounds
• Higher values (e.g., 0.01) = less sensitive, requires louder music

Troubleshooting

Audio Issues

• Raspberry Pi: Check that your audio input is working with: arecord -l
• macOS: Check System Preferences > Sound > Input to ensure microphone is working
• Multiple devices: If you have multiple audio inputs, select the right one:

  python select_input.py

• Adjust silence_threshold if the script is too sensitive or not sensitive enough

General Issues

• Check the log file for detailed error messages
• Ensure internet connectivity for Shazam API calls
• If you encounter permission issues, make sure the scripts are executable: chmod +x *.sh

macOS Specific

• If you get "portaudio" errors, make sure Homebrew installed it correctly: brew list portaudio
• If tkinter GUI doesn't work, install python-tk: brew install python-tk
• If you get permission errors with Homebrew, you may need to run: sudo chown -R $(whoami) /usr/local/var/homebrew
• If you get "pyaudioop" errors on Python 3.13+, the script includes a compatibility module
• If you get FFmpeg warnings, install it with: brew install ffmpeg

Python 3.13+ Compatibility

The script includes pyaudioop_compat.py to handle the removal of the pyaudioop module in Python 3.13+. This is automatically loaded when needed.

Virtual Environment Management

The project uses a virtual environment to isolate dependencies:

• Virtual environment location: music_env/
• Activation: source music_env/bin/activate
• Deactivation: deactivate
• Reinstalling dependencies: pip install -r requirements.txt (while activated)

Dependencies

• pyaudio: Audio recording
• numpy: Audio processing
• shazamio: Shazam API integration
• Pillow: Image processing for cover art
• requests: HTTP requests for downloading images
• tkinter: GUI (usually included with Python)